I'll add my stories to the 2 brother comments, in my prepa my best friend was by far the best in class. He did the 2 year program in chemistry in the first 2 months by himself. He arrived once in exams after a full night of re-reading the 3 LOTR books and still nailed the best grade effortlessly. And to his own admission, he was far from the most productive / smarter guys he knew.
I remember listening to him and a teacher, the teacher would give some anecdotes on what he's seen at the ENS. People reciting world chess championship games at night to fall asleep. Reading massive math books (1000+ pages) in an afternoon. Another story I heard in a different context from another teacher, math students were assigned a python project, after an introductory course. They never did any programming before. One student wrote 300 LoC in a single function and showed it to the teacher. It didn't have a main function, so the teacher asked him how he tested it. The student didn't know what he was talking about. They added what's needed to run the function and it worked.
So, it still begs the question... "How ?" Or, more precisely: "How the f... ?"
Clearly this goes beyond "Grit" [1], here, right ? (Those people do not seem like they have to coerce themselves into focusing that much.)
Is there a known (somewhat rigorous or not) study of those "super geniuses" ? I know that the "memory champions" are covered in "Moonwalking with Einstein" [2] ; but that seems like a different beast...
Ah, I wouldn't know of any actionnable way to unlock this for yourself unfortunately. I think those people are gifted. There is definitely research (and documentaries around that research), you can look for Julian Stanley "Quick learners" or Maryam Mirzakhani and there are of course plenty of it. But again, it's not actionnable to watch a 13yo solve a very hard problem in 4 different ways in 20 minutes.
Unfortunately I think it is as much a curse as it is a gift. One of my parents' friend is a math researcher. He is not at the absolute end of the spectrum, but he is the kind of people who will write on the bathroom walls because he has an idea NOW and it cannot wait a minute to explore. He forces himself to do competitive cycling and can't enjoy more casual hobbies because if he does not spend 100% of his energy and focus to something, his brain will just do math.
It is. Probably an even greater gift to earth from the NetBSD community than NetBSD itself. The ability to run recent packages on most arch without them forcing you to use NetBSD, but allowing you to keep the original OS in many cases if you want, is mind-blowing.
As an SRE/ops (and I'm talking some years ago) it was often a pain point, especially with devs with a "works on my machine" attitude ; you would never get the exact requirements from them, I even saw a team of 2 who worked together with different versions of stuff on their respective machines. I also worked in some "offline" environments where once in prod you cannot pull anything from the internet, and you cannot install a compiler too, so it's quite hard to ship because some pip packages require to be built.
I found a way using (can't remember the tool name) which if you loop through the imports and gives it to the tool you get the package name, then I would build wheels to have all binaries and build a container or a VM with all that's needed, thus working completely around python package managers. This was a good enough workflow for the kind of deployment we needed.
Jupyter added a layer of complexity, I deployed it alongside RStudio as browser IDEs in docker swarm. Everybody wants a different set of deps and versions, so you have to keep track of everything, and also people may use things just for development that must not be shipped to prod, so you have to keep track of that too. Also some would develop notebooks on windows and expect them to work in linux VMs/containers and even in prod.
Nowadays devs ship container images anyway through a CI so it is less of an issue. In this era docker was far from being the de-facto everywhere, some people were still afraid of this, security didn't like it, etc.
I'm glad that my country is doing this. On one hand, we have free healthcare and there is the argument that we don't need this and that it's just a way to save money on the weakest of us all. But in practice it is not the case.
I have 2 grandfathers who have been denied certain surgeries because they are too old, not because it would be dangerous, but because there are waiting lists of several years and they never get priorities. Now, none of them are in a hurry to use this procedure of course (only one mentionned going to Switzerland when he almost lost total mobility, but of course cannot afford it), but both of them are in pain, and when it will become excruciating and quality of life will converge to 0, I feel it is a much better prospect than staying for weeks in a hospital room, suffering despite the morphine, with the spouse having to book taxis for visits because of course nobody is going to pay for that.
We are talking about people who have enjoyed near 40 years of happy retirement and a slow but very steady health decline at the end, with lots of time to think and discuss this topic. To me it's a relief to think that I will have this option for myself eventually.
I'm surprised you said he couldn't afford Switzerland, I thought they weren't supposed to make money off help with dying? Are they secretly making money then, or is there paperwork that's expensive to file?
The last time I checked Switzerland was still your best bet to exit with dignity rather than spending the last several years of your life as a bedridden vegetable kept barely alive with drugs, like several of my relatives were. As an (apparently) rational person I really can't fathom why we put people through this slow torture, is it based on some medieval religious superstition or something?
Sure, but a prediction made 3 months ago turns out to be short by a few percent at most, and that leads to a 25%+ drop in the share price? That seems weird to me.
What if the market expected 25% more then reported ? Nobody "knows" what the market expects. People infer it by looking at forward valuation, company guidance, investor expectations, and many many other things happening in the world, in competition, in the value chain. And of course the market does its thing and figures that this company has x% chance of beating (or missing) by $y, and when it's wrong the moves can be huge.
IME you have to be true to what you predict. Whether you're predictably growing, predictably shrinking, or predictably flat if you blow your prediction that's when people start to worry that you don't know what you're doing.
Especially when the expectations are informed by the company’s own guidance about what to expect and they are wrong. It means they missed their own predictions which doesn’t engender confidence.
A few things to note. 1 billion isn't a thousand times a million. If you make a conservative 5% let's say out of your net worth, you still need to work with a million, whereas you don't with a billion. So, technically, $400 with a million is some amount of work hours, whereas $400k with a billion is just pocket change taken out of more than most people lifetime's of earnings that is just 1 year of your interest.
Also, a lot more people (more than 1000x) have $400 to give than $400k so in a sense if people with $400 to give were all being very generous, they could amount to a lot more than what billionnaires could give.
The point they were trying to make was that if you take appreciation of assets into account, if your billion is appreciating by a relatively modest 5% per year, you are passively earning 50 million/year. Whereas someone with one million passively earns 50 thousand/year. One is enough to live in luxury anywhere in the world for several lifetimes, the other is enough to live comfortably in some parts of the US (or like a king in many parts of the world) but not enough to throw 6 figures at a programming language foundation for fun.
This is a common but silly claim; there is, generally speaking, no such thing as a safe rate of return that overcomes the inherent losses due to inflation. If you're getting a 5% rate of return on cash, that comes with both risk (someone with a billion dollars isn't going to benefit from FDIC insurance) and doesn't even overcome basic inflation.
That $50 million a year is also subject to income taxation and cannot be easily avoided. $50 million a year in interest on returns from cash will be hit at the 37% marginal rate, plus whatever the state assesses, so north of 50% in California.
Or to take an intermediate value, $10 million is 500k a year and most people will find it difficult to spend that much on themselves, so it’s going to grow on its own and compound. It will grow more rapidly if some is invested in the stock market.
Also, donating appreciated stock avoids taxes. This donation may have come out of a donor-advised fund.
Rich people can make substantial charitable donations rather easily and make a big difference. I suggest we encourage them.
Ah there is liquidity too, but your brother comment makes my point clearer.
About liquidity, yes most people with a million net worth actually have more than half in their house, so technically it is much harder for them to throw cash than somebody with a billion and a much smaller % of their worth in illiquid assets such as property or unlisted companies. I wish I had made this point too.
Uniformity ? Try deploying openbao inside kube, if kube decides to restart your pods, you're in for unsealing them at 3am, waking up everybody who owns a Shamir key. So bao stays out of the cluster, or pinned to certain nodes, defeating the purpose entirely. Also, with the ultra wide variety of tools at every layer of the stack, uniformity is a joke ; there are no 2 kube cluster deployment that are the same really.
Standardized knowledge ? The operating system is standardized knowledge. Any competent SRE should be able to login into a Linux box and figure out what's running there. And if you let your previous ops shadow it all you're just a pretty bad CTO.
Tracing who does what ? First of all anybody with admin access can run one time jobs just like anybody with sudo can run one time commands. That's like chapter 01 of the kube doc. Also again at the kube layer itself, below the helm chart, the ops who set that up or updates it can and will change stuff that breaks stuff.
Kube isn't necessarily bad and has it's purpose but it's not a product. It's like Linux, a complex piece of tech that requires a lot more knowledge than "just push this helm chart" to work.
Sounds like you had specific issues with openbap and your cluster provider. Whatever the tech stack it's all presented the same way and easily discoverable.
Kubernetes is a cloud operating system- this is exactly the point about standardized knowledge.
I give a counter example to a general statement, in logic, it is enough to debunk the original statement. My point is, SOME things wouldn't run predictably inside the cluster (in that case without pinning to nodes, which the article says isn't necessary, and which in general defeats the purpose), so you'd need to run some things outside of it.
As per standardized knowledge, I can't see how somebody even proficient with kube, could jump into any app and troubleshoot bad behavior. Apps each have their quirks and subtleties, specific components that behave a certain way. The layers still exists, the kube cluster itself (which again has many component options at every layer of the stack ; hard to know them all), and the app (which will require at least some specialty knowledge).
If it's just about pushing helm charts we wouldn't need SRE anymore, just a CI.
The same way you're describing sysadmins knowing how to look at a linux system and understand what's going on. I feel exactly I can jump into any app and troubleshoot on k8s. And I draw on a lot on top of my previous sysadmin exp.
The debugging? Not really. It comes from sysadmining. But k8s is a standardized way to deploy software amongst a fleet of machines. Which makes it easy to debug complex systems because I know how to access it all.
Alpine is (was ?) a Renault brand, which is a French company, so it is a little less exotic than a Japanese police force buying a German car (Japan being such a massive car exporter themselves).
I remember listening to him and a teacher, the teacher would give some anecdotes on what he's seen at the ENS. People reciting world chess championship games at night to fall asleep. Reading massive math books (1000+ pages) in an afternoon. Another story I heard in a different context from another teacher, math students were assigned a python project, after an introductory course. They never did any programming before. One student wrote 300 LoC in a single function and showed it to the teacher. It didn't have a main function, so the teacher asked him how he tested it. The student didn't know what he was talking about. They added what's needed to run the function and it worked.
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